Digital identity systems allow computer users to establish a base set of credentials, and to build multiple “personas” on top of the base credentials. For example, user's base credentials might include information such as name and default email address. Separate “work” and “home” personas could build upon and customize the base data, by adding information such as work and home phone numbers, non-default (e.g., private or specialized) email addresses, etc.
If a user whishes to exchange identity information in a given context, the user is currently required to pick and/or edit the persona to use manually. For example, a user could decide to use a previously configured work persona to provide contact information to a colleague while attending a work-related event. While this is sufficient in very general cases, it is neither flexible nor ideal.
For example, suppose a user is attending a large industry conference, and has a local, conference-specific hotel room number, telephone extension and temporary email address. The user may wish to provide this event-specific data as contact information to others at the conference. As such, neither the user's work nor home persona would be appropriate in this context. Instead, the user would have to manually configure a new persona with the conference-specific information. While a user might manually construct a small number of personas, construction of event-specific or other fined grained personas would require excessive effort on the part of the user.
Furthermore, even given a large number of existing personas, the transaction context alone might not provide sufficient information to aid the user in the selection of the correct persona to use. Environment context information is often required as well. For example, the phone number a user might distribute in a work related context could differ at an internal meeting (e.g., the local extension) versus an external meeting (e.g., the full number including the area code).
Therefore, it would be desirable to be able to automatically discover a current environmental context, and leverage this information to at least partially automate construction of digital personas for identity exchanges.
Additionally, while there exist rich technologies to exchange identity information in the digital world, the physical world is more limited. Currently a user wishing to exchange identity information physically is limited to either using pre-printed business cards or manually constructing one (i.e., by writing on paper). The use of pre-printed business cards limits flexibility. Whatever information is on the card must be used in all situations, and cannot be tailored to fit the current context (e.g., event, location, language). The latter method, while more flexible, requires significantly more effort, and is often limited by the capability of the user (i.e., does the user know Japanese?). Nonetheless, identity information exchange is often necessary in the physical world (for example, due to lack of digital communication devices, rules governing device use, etc.).
Neither of the two existing methods allow any coupling to a digital identity system. Thus, a user who has a rich set of digital identity information has no way to easily generate physical tokens based on this digital data. Therefore, it would also be desirable to allow real-time generation of physical tokens based on contextual and environmental digital identity data.